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All Journal JUTIK : Jurnal Teknologi Informasi dan Komputer Jurnal Intelek Insan Cendikia
Paskah Abadi Simanullang
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Religion Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences

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RANCANG BANGUN WEBSITE PENGELOLAAN BUKU DIGITAL BERBASIS NATURAL LANGUAGE PROCESSING (NLP) Rangga Wahyu Pratama; Paskah Abadi Simanullang; Peter Tymoty Hutabarat; Revidamurti Daulay; Adidtya Perdana
Jurnal Teknologi Informasi dan Komputer Vol. 11 No. 1 (2025): JUTIK : Jurnal Teknologi Informasi dan Komputer, Edisi April 2025
Publisher : LPPM Universitas Dhyana Pura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36002/jutik.v11i1.3755

Abstract

A digital book management system has become a crucial solution in the digital era, helping users efficiently organize and search their book collections. In the context of information technology advancements, the demand for an integrated platform that can store book data and provide easy access through metadata-based search features is increasing. However, the main challenge lies in the absence of a system that supports automatic information extraction from digital book files and searches based on criteria such as title, language, or topic. To address this issue, this study employs the Research and Development (R&D) method to design the system, a literature review to analyze NLP technology, and observations to understand user needs. The research results in an application built with PHP, MySQL, and Python (NLP), featuring file uploads, automatic metadata extraction, search based on specific criteria, and user profile management. The study concludes that the developed system provides a practical and efficient solution for digital book management, with a modular design that supports scalability and further development.
Integrasi Algoritma Firefly dalam Optimasi Hyperparameter CatBoost untuk Prediksi Risiko Penyakit Paru-Paru Felix John Pardamean Hutabarat; Paskah Abadi Simanullang; Revidamurty Daulay; Adidtya Perdana
Jurnal Intelek Insan Cendikia Vol. 2 No. 12 (2025): Desember 2025
Publisher : PT. Intelek Cendikiawan Nusantara

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Abstract

Penelitian ini menyajikan suatu pendekatan terintegrasi untuk meningkatkan prediksi risiko penyakit paru-paru melalui optimasi hyperparameter CatBoost menggunakan Algoritma Firefly. Dengan memanfaatkan dataset yang terdiri atas 30.000 sampel yang mencakup atribut demografis, perilaku, dan klinis, penelitian ini menerapkan metodologi CRISP-DM guna memastikan proses pengolahan data dan pengembangan model yang sistematis. Algoritma Firefly digunakan untuk mengeksplorasi ruang pencarian hyperparameter dan menentukan konfigurasi terbaik berdasarkan nilai F1-score melalui validasi silang 5-fold, sehingga menghasilkan model CatBoost yang mengalami peningkatan kinerja secara signifikan dengan capaian akurasi sebesar 94,33%, presisi 100%, recall 88,15%, F1-score 93,70%, serta AUC-ROC sebesar 0,9926. Hasil penelitian menunjukkan bahwa Algoritma Firefly mampu meningkatkan kinerja dan stabilitas CatBoost, sehingga menghasilkan model prediktif yang andal untuk mendukung deteksi dini dan pengambilan keputusan klinis terkait risiko penyakit paru-paru
Co-Authors Adidtya Perdana, Adidtya Felix John Pardamean Hutabarat Peter Tymoty Hutabarat Rangga Wahyu Pratama Revidamurti Daulay Revidamurty Daulay